w a t e r r e s e a r c h 7 7 ( 2 0 1 5 ) 1 3 e2 3
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Integrated experimental investigation and mathematical modeling of brackish water desalination and wastewater treatment in microbial desalination cells Qingyun Ping a, Zuyi Huang b, Carlos Dosoretz c, Zhen He a,* a
Department of Civil and Environmental Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA b Department of Chemical Engineering, Villanova University, Villanova, PA 19085, USA c Faculty of Civil and Environmental Engineering, Technion-Israel Institute of Technology, Haifa 32000, Israel
article info
abstract
Article history:
Desalination of brackish water can provide freshwater for potable use or non potable ap-
Received 10 December 2014
plications such as agricultural irrigation. Brackish water desalination is especially attrac-
Received in revised form
tive to microbial desalination cells (MDCs) because of its low salinity, but this has not been
8 March 2015
well studied before. Herein, three brackish waters prepared according to the compositions
Accepted 10 March 2015
of actual brackish water in three locations in Israel were examined with domestic waste-
Available online 20 March 2015
water as an electron source in a bench-scale MDC. All three brackish waters could be effectively desalinated with simultaneous wastewater treatment. The MDC achieved the
Keywords:
highest salt removal rate of 1.2 g L1 d1 with an initial salinity of 5.9 g L1 and a hydraulic
Microbial desalination cells
retention time (HRT) of 0.8 d. The desalinated brackish water could meet the irrigation
Microbial fuel cells
standard of both salinity (450 mg L1 TDS) and the concentrations of major ionic species,
Brackish water
given a sufficient HRT. The MDC also accomplished nearly 70% removal of organic com-
Wastewater
pounds in wastewater with Coulombic efficiency varied between 5 and 10%. A previously
Mathematical model
developed MDC model was improved for brackish water desalination, and could well predict salinity variation and the concentrations of individual ions. The model also simulated a staged operation mode with improved desalination performance. This integrated experiment and mathematical modeling approach provides an effective method to understand the key factors in brackish water desalination by MDCs towards further system development. © 2015 Elsevier Ltd. All rights reserved.
1.
Introduction
Because of the world-wide water shortage and local water scarcity, desalination has been increasingly considered as a * Corresponding author. Tel.: þ1 540 231 1346; fax: þ1 540 231 7698. E-mail address: [email protected] (Z. He). http://dx.doi.org/10.1016/j.watres.2015.03.008 0043-1354/© 2015 Elsevier Ltd. All rights reserved.
viable approach for freshwater supply (National Research Council, 2008). The recently emerged microbial desalination cell (MDC) appears to be a promising alternative or supplement for traditional desalination technologies. An MDC
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converts the energy stored in wastewater directly into electricity by microorganisms and utilizes it in situ to drive desalination in a process similar to electrodialysis (ED) (Cao et al., 2009). The difference between MDC and ED is the source of electrons and energy consumption: an MDC uses the electrons released by microbial oxidation of organic compounds, while an ED is driven by electrons from water oxidation; as a result, an MDC does not necessarily require external voltage, but an ED must be applied with a high external voltage or current. The MDC has been advanced with reactor configurations, such as stacked reactor (Kim and Logan, 2011; Chen et al., 2011; Ge et al., 2014), decoupled reactor (Ping and He, 2013), and upflow tubular reactor that has demonstrated a salt removal efficiency >99% (Jacobson et al., 2010, 2011). Optimized operation through recirculation between the anode and the cathode compartments could achieve pH balance without the addition of costly buffer (Chen et al., 2012; Qu et al., 2012). Fundamental studies have also been conducted to reveal the diverse microbial community in the anode of MDC (Luo et al., 2012a). Recently, MDCs have been scaled up to a total liquid volume of 105 L, which encourages further development of this technology (Zhang and He, 2015). Although MDCs can achieve desalination without external voltage applied, its desalination requires a fairly long time because of slow microbial oxidation, compared with electrochemical oxidation of water in ED. The low desalination rate of MDCs indicates that this technology may be more suitable for application as a pre-desalination process for conventional desalination such as RO (reverse osmosis) or ED (Zhang and He, 2012). Another potential application of MDC technology is to desalinate low-salinity water, such as brackish water that has TDS (total dissolved solids) in the range of 1000 to atsah, 1972), or the treated waste10,000 ppm (Levite and Mo water. In many arid parts of the world, the local aquifers that contain brackish water are the main source of freshwater. It is of great importance to desalinate brackish water for municipal or agricultural applications. ED and EDR (electrodialysis reversal) are the current technologies for treating brackish water with TDS up to 3500 mg L1; a higher salinity significantly increases the energy consumption compared with RO (USBR, 2003). The salinity in brackish water comes from two sources: dissolution of minerals, and natural mixing of seawater with groundwater in coastal aquifers (National Research Council, 2008). Most brackish water cannot be directly used for drinking purpose or irrigation due to the high salinity, and specific ion toxicity for plants or the possibility of deteriorating soil conditions (Rhoads et al., 1992). There have been several MDC studies that examined desalination of synthetic salt solution with salinity similar to brackish water (Luo et al., 2012c; Zuo et al., 2013). The study of actual brackish water was reported only in a previous work that focused on the softening of hardness in several groundwater samples (Brastad and He, 2013). The transport behavior of multiple ions across ion-exchange membranes were studied at the same initial molar concentration with only one kind of counter ion (anion/cation) (Luo et al., 2012b); however the results cannot be applied to predict the ion composition in the actual brackish water desalination where the individual ion has different concentration. The transport rate of individual ions is a product of mobility (affected by hydrated radius and ionic
charge) and ion concentration (Strathmann, 2004), while the previous study only considered hydrated radius as influencer. Clearly, there is a lack of detailed analysis and understanding of removal of different ionic species during desalinating actual brackish water or saline water with more complicated composition than NaCl solution in MDCs. To assist the interpretation of the data obtained from the bench studies and to provide guidance for system operation, mathematical models of MDCs treating brackish water will be very valuable. Recently, the first MDC model was reported and it could effectively predict MDC performance under different operating conditions (Ping et al., 2014). However, the model did not well predict the change in salt concentration, likely related to that the low current efficiency, which mostly occurs when maximum current is not reached, was neglected in the model development. Desalinating brackish water in an MDC by using the energy obtained from domestic wastewater comes with two issues: low organic strength in the anode compartment, and low salinity in the desalination compartment, both of which will lead to current deviating from normal values and the low current efficiency due to low current generation. In addition, diffusion element in the previous model might not work for brackish water considering the difference in salt concentration across ion exchange membranes. Therefore, the previously developed MDC model must be improved with new information obtained from brackish water desalination. In this study, we have adopted an integrated approach of experimental investigation and mathematical modeling to study brackish water desalination in bench scale MDCs. Three synthetic brackish waters were prepared with the recipes to mimic actual brackish water in three locations in Israel. Actual domestic wastewater (primary effluent) was used as an anode substrate to provide driving force for desalination. The objectives of this study were: (1) to demonstrate the MDC performance treating brackish water and actual wastewater; (2) to understand the removal of different ionic species during desalination; and (3) to improve the MDC model for brackish water desalination by incorporating junction potential, current efficiency, restricted diffusion, and osmotic flux. The model was calibrated with steady state values and validated by experimental data of both dynamic and steady state conditions.
2.
Materials and methods
2.1.
MDC setup and operation
The MDC was constructed as a tubular reactor similarly to the one in the previous study (Ping et al., 2014), consisting of two layers of ion exchange membranes (IEM): anion exchange membrane (AEM, AMI-7001, Membrane International, Inc., Glen Rock, NJ, USA) with a 3.8-cm diameter and 20-cm length formed the anode compartment (300 mL), and cation exchange membrane (CEM, CMI-7000, Membrane International, Inc.) that had a diameter of 5 cm and a length of 20 cm wrapped the AEM tube and created a space between the two membrane tubes forming a desalination compartment (150 mL) (Fig. S1, supplementary information). The distance
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between the AEM and the CEM was 0.6 cm. The anode electrode was a 20-cm long carbon fiber brush, and the cathode electrode was a piece of carbon cloth coated with activated carbon supported platinum (Pt/C) as a catalyst at a loading rate of 0.2 mg Pt cm2. An external resistor of 0.1 U connected the two electrodes by using titanium wire. The anode feed solution was the primary effluent from a local wastewater treatment plant (Peppers Ferry, Radford, VA, USA), and amended with 500 mg L1 of glucose. The modified wastewater contained a COD (chemical oxygen demand) concentration varying between 500 and 650 mg L1. Three brackish waters were prepared by dissolving different salt compounds into tap water according to the composition shown in Table 1. The catholyte was prepared same as the brackish water used in the desalination compartment, dripping from the top to the bottom of the outer (CEM) tube for rinsing the cathode electrode and recirculated from a 9-L reservoir at a recirculation rate of 35 mL min1. The anolyte had a feeding rate of 0.5 mL min1, resulting in a hydraulic retention time (HRT) of 10 h, and was recirculated at 100 mL min1. The brackish water was fed into the desalination compartment without recirculation at three flow rates, 0.015 mL min1 (HRT of 6.9 d), 0.06 mL min1 (HRT of 1.7 d), and 0.13 mL min1 (HRT of 0.8 d) for the brackish water A, or 0.06 mL min1 (HRT of 1.7 d), 0.13 mL min1 (HRT of 0.8 d), and 0.3 mL min1 (HRT of 0.35 d) for the brackish waters B & C.
2.2.
Measurement and analysis
The MDC voltage was recorded every 3 min using a digital multimeter (Keithley Instruments, Inc., Cleveland, OH, USA). The conductivity of the salt solution was measured using a benchtop conductivity meter (Mettler-Toledo, Columbus, OH, USA). The chemical oxygen demand (COD) was measured using a colorimeter according to the manufacture manual (Hach Company, Loveland, CO USA). The ion compositions in the solution were measured using ion chromatography (Dionex DX-500) with suppressed conductivity detection. The column used for cations was a CS-16 with a CSRS-300 suppressor and for anions was an AS-9HC with an ASRS-300 suppressor. The TOC (total organic carbon) of the samples was measured by Shimadzu Scientific Instruments TOC-VCP with combustion catalytic oxidation/NDIR detection method. The salt removal rate was calculated as the removed salt concentration divided by HRT.
Table 1 e The concentrations of major ions (mg L¡1) in three brackish waters. Brackish water composition Ca2þ Mg2þ Naþ Kþ NHþ 4 HCO 3 SO2 4 Cl NO 3 TDS
A
B
C
742 207 1054 26 0.0 92 781 2942 3.5 5887.7
105 78 364.5 5.3 0.0 405 88 620.3 65.6 1540
71.7 56.1 235 3.7 0.0 369.4 68 366 50 1068
3.
Model improvement
3.1.
Electricity generation
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Junction potential created by concentration gradient across the IEM is an additional potential source responsible for the ion-separation besides the potential difference created by electrode reactions. In an MDC treating wastewater and seawater, the junction potential is up to 0.2 V. For brackish water desalination, when the salt concentration in the desalination compartment is reduced lower than in the anolyte or catholyte, the junction potential poses a negative effect on the current generation, In this updated model, the junction potential is defined as (Kim and Logan, 2013): Vjct ¼
RT X tAEM;ion aion;m RT X tCEM;ion aion;m ln ln þ F ion zion F ion zion aion;a aion;c
(1)
where tAEM,ion and tCEM,ion are the transport number of ionic species in AEM and CEM, zion is the ionic charge, aion,m, aion,a, and aion,c are the ionic activity in the desalination, anode, and cathode compartments, F is the Faraday constant (96,485 A s mol1), R is the ideal gas constant (8.31 J K1 mol1), and T is the MDC temperature (298.15 K). In an MDC, the junction potential can be roughly estimated by assuming that the activity ratio equals the total dissolved solids ratio. The ideal tNaþ and tCl will be 0 and 1 for AEM, and 1 and 0 for CEM. The MDC current is then calculated as: IMDC ¼
VOC OPconc þ Vjct ðRext þ Rint Þ
(2)
where VOC is the open circuit cell voltage that depends on the anodophilic microorganism concentration, OPconc is the concentration overpotential and Rint is the internal resistance of the MDC, which were defined in the previous study (Ping et al., 2014). Rext is the applied external resistance.
3.2.
Mass balance of salt in MDCs
To better show the removal of individual ions in brackish water, the present model takes milliequivalent ions per liter (meq L1 ¼ mg L1 / equivalent weight) as the unit for salt concentration instead of mol L1 in the previous model. We incorporate in the present model the current efficiency a, which shows the ratio between the coulombs harvested from the movement of salt ions and the coulombs harvested from electrical circuit. The ideal situation is that one mole of electrons would take away two molar-equivalents of ions, which means that a is equal to 1. However, it was observed in our previous study that an MDC usually exhibits low current efficiency when the maximum current is not reached. Thus, we proposed an inverse tangent function to present the relationship between current and a. a begins with a zero value, increases sharply, and levels off upon the increase of IMDC from zero. The small value of a for a low IMDC is able to relax the assumption made in the previous model in which a was always equal to 1. a¼
arctanðIMDC *1000 Ira;max *1000Þ þ arctanðIra;max *1000Þ arctanðIa¼1 *1000 Ira;max *1000Þ þ arctanðIra;max *1000Þ
(3)
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where IMDC is the current generated by the MDC, Ira,max is the current when da/dI is the greatest and needs to be estimated from experimental data, and Ia¼1 is the current when a ¼ 1. A profile of a is shown in Fig. S2A. The water transport across an IEM is another important factor that contributes to the reduced salt concentration in the desalination compartment. The water flux between the desalination compartment and the anode and cathode compartments is represented by an osmotic pressure model, and the osmotic pressures in the solutions were calculated in accordance with the Van't Hoff's equation: Jw;a ¼ AAEM $RTiðCsalt;m Csalt;a Þ 2
(4)
Jw;c ¼ ACEM $RTiðCsalt;m Csalt;c Þ 2
(5)
where, Csalt,m, Csalt,a, and Csalt,c are the salt concentrations in the desalination, anode, and cathode compartments (meq L1), respectively. AAEM and ACEM stand for the water permeability of anion and cation exchange membranes (L day1 atm1), respectively. i is the Van't Hoff factor that reflects the number of discrete ions when compounds dissolve in water and was approximated to be 2 for salt NaCl in the present study. Diffusion of salt molecules from high concentration to low concentration is greatly smaller in the opposite direction of current-driven ion movement and does not follow a linear relationship of the salt concentration difference as defined by the previous model. Therefore, to make concentration difference less influential when the salt concentration in the desalination compartment is less than in the anode or cathode compartment, the diffusion was modified to restricted diffusion functions Dres,a and Dres,c by an inverse tangent function. The profile of diffusion is shown in Fig. S2B.
where Qsalt and Qanode are the flow rates (L day1) of the salt solution in desalination compartment and of anolyte in the anode compartment. Vsalt, Vanode, and Vcathode are the volumes of the desalination, anode, and cathode compartments. Csalt,in and Csalt,a,in are the salt concentration in the salt influent and anolyte influent (meq L1). Dsalt and Danode are the dilution rates (day1) in the desalination compartment and anode compartment defined in the previous model quantified by the ratio of the flow rate over the volume of the compartment. d is the membrane salt transfer ability (g L1 day1). The first and second terms of Equations (8) and (9) represent the cause of concentration change by inflow and outflow of solutions. The third term in Equations (8) and (9), and the first term in Equation (10) represent the current-driven movement of ions. The last two terms in Equation (8) and the last terms in Equations (9) and (10) show the diffusion between the three compartments. The volume ratios of desalination compartment to anode or cathode compartment were considered for the rate change of Csalt,a, and Csalt,c. To show the individual ion concentration in the salt solu2 tion, such as Naþ, Kþ, Mg2þ, Ca2þ, Cl, NO 3 , SO4 , the following equations are needed. dCion;m Qsalt þ Jw;a þ Jw;c ¼ Dsalt $Cion;in $Cion;m dt Vsalt IMDC 4ion $ $a þ d$Dres;a þ d$Dres;c F$Vsalt
where Cion,in, and Cion,m are the individual ion concentration in the salt influent and desalination compartment, and ion refers to any anion or cation according to the ion composition in the salt influent. 4ion is the ratio defined as
Dres;a ¼ ½arctanððCsalt;m Csalt;a Þ 2,50 piÞ þ arctanðpiÞ
(6)
u$Canion;m 4anion ¼ P u$Canion;m
Dres;c ¼ ½arctanððCsalt;m Csalt;c Þ 2,50 piÞ þ arctanðpiÞ
(7)
or
The previous model assumed that only NaCl will cause concentration-gradient-driven-diffusion of salt, and excluded the contribution of current-driven movement of ions to the salt concentration change in the anode and cathode compartments. In the case of brackish water desalination, where the concentration difference could be very small and even negative, it causes large discrepancy from the experimental data. Concerning the above facts, the updated equations for concentration change in the desalination compartment, the anode, and the cathode compartments were modified as Equations (8)e(10): dCsalt;m Qsalt þ Jw;a þ Jw;c IMDC ¼ Dsalt $Csalt;in $Csalt;m 2$ $a dt Vsalt F$Vsalt 2d$Dres;a 2d$Dres;c
Qanode Jw;a dCsalt;a IMDC ¼ Danode $Csalt;a;in $Csalt;a þ 2$ $a Vanode dt F$Vanode Vsalt þ 2d$Dres;a $ Vanode dCsalt;c IMDC Vsalt ¼ 2$ $a þ 2d$Dres;c $ dt F$Vcathode Vcathode
u$Ccation;m 4cation ¼ P u$Ccation;m
dCsalt;m X dCion;m ¼ dt dt
(12b)
(13)
Parameter estimation
Parameter estimation was performed with fmincon subroutine in Matlab to search a local minimum of objective function defined as normalized room-mean-square-error (RMSE) for dynamic data:
(9)
rffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 PN yi b yi i¼1 RMSE ¼
(10)
(12a)
where u is the mobility of ions in solution (Vanysek, 2002). Equation (8) is then modified to Equation (13) by summing up the individual ion concentration in the salt solution acP cording to the relationship Cion,m ¼ Csalt,m, and P Cion,in ¼ Csalt,in.
3.3. (8)
(11)
N
bÞ maxð y
Or squared error (SE) for steady sate data:
(14)
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SE ¼
sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi bi 2 yi y b y
17
(15)
^i and yi represent experimental data and model prewhere y dicted values at tj or at steady state. Constraints were set to satisfy the true yield range for anodophilic microorganisms between 0.027 and 0.054 mg-Biomass mg-COD1 (Marcus et al., 2007).
4.
Results and discussion
4.1.
Wastewater treatment
The MDC effectively treated wastewater with little influence from the different salinity of brackish waters or current generation. With the initial COD concentration of 500e650 mg L1 (varied due to variation of organic concentration in actual wastewater), the MDC removed the COD of 421 ± 85 mg L1, resulting in a final COD concentration of 80e262 mg L1 and the COD removal rate of 68.9 ± 10.7%. Current generation was affected by the salinity (or conductivity) of the brackish water. The MDC generated 12.3 ± 2.4 A m3 when treating the brackish water A, which had the highest initial salinity of 5.9 g L1 of TDS among the three brackish waters. Consequently, higher Coulombic efficiency (of 10.9 ± 0.9%) was observed with the brackish water A. For comparison, the brackish waters B (1.5 g TDS L1) and C (1.1 g TDS L1) resulted in lower current generation of 8.1 ± 0.5 A m3 and 7.5 ± 1.0 A m3, respectively; they also had lower Coulombic efficiency of 5.7 ± 0.6% and 5.6 ± 1.2%, respectively (Fig. 1). The lower Coulombic efficiency with treating the brackish waters B and C, along with similar COD removal performance (to that with the brackish water A) indicated that, with decreased conductivity in the desalination compartment, the portion of COD used for electricity generation also decreased. Nonanodophilic microorganism played an important role in removing COD, especially when the current generation was suppressed, thereby maintaining a comparable COD concentration in the final effluent. When the initial organic strength in wastewater was increased to ~1162 mg L1 by adding more glucose for desalinating the brackish water A, the current was not improved. In fact, it was observed that the increased COD strength lowered Coulombic efficiency to 5.8% (Fig. 1) and resulted in a higher effluent COD of 524 mg L1. Those results suggest that the present MDC system was not limited by the anode activity and electron source; instead, the limiting factors that resulted in low CE might come from the low conductivity in both the wastewater and the desalination compartment, and complex substrates that led to competing electron sinks (Lee et al., 2008).
4.2.
Brackish water desalination
4.2.1.
General desalination performance
The MDC accomplished desalination of the tested brackish waters, affected by both salinity and HRT of brackish water. At the same HRT of 0.8 d (salt flow rate of 0.13 mL min1), the MDC decreased the conductivity by 19.6% in the brackish water A, while the conductivity reduction in the brackish
Fig. 1 e Coulombic efficiency of the MDC at different current densities when desalinating three types of brackish waters.
waters B and C was much higher at 43.4 and 57.4%, respectively (Fig. 2A). Increasing the HRT to 1.7 d (salt flow rate of 0.06 mL min1) significantly improved the conductivity reduction to 33.3 ± 7.2% for the brackish water A; meanwhile, the MDC further improved the desalination of the brackish waters B and C to 82.5 ± 5.0 and 88.1 ± 0.9%, respectively. To achieve desalination of >90% for the brackish water A, the HRT must be increased to 7 d. It was observed that higher desalination efficiency was obtained at a longer HRT and the trend became more distinct as the initial salinity decreased (Fig. 2A), suggesting that the treatment time had a greater influence on desalination because of the limited desalination capacity of the present MDC. Salt removal rate, on the other hand, exhibited a different trend from desalination efficiency (or conductivity decrease) (Fig. 2B). At the HRT of 0.8 or 1.7 d, the salt removal rate increased for brackish waters C, B, and A (0.75, 0.80, and 1.2 g L1 day1; or 0.52, 0.74, and 1.1 g L1 day1) as the initial salinity increased (C < B < A). Relatively higher salt removal rate was also observed with a shorter HRT (Fig. 2B). The accelerated desalination with higher initial salinity or shorter HRT was because of the resulted higher conductivity in the desalination compartment (as well as the salt effluent) that led to a lower internal resistance and thus higher current generation that drove desalination. The slightly lower salt removal rate of treating brackish water C at HRT of 0.35 d than that at 0.8 d was likely due to the low current of 6.4 A m3 compared with 7.5 A m3. The higher conductivity of 1.2 mS cm1 (0.35 d) compared with 0.7 mS cm1 (0.8 d) did not lead to higher current generation, indicating that some factors other than electrolyte conductivity (resistance) limited the MDC performance. Given sufficient retention time, the MDC could reduce the salinity to a very low level. For example, at the HRT of 1.7 d, the TDS of the brackish water C was decreased to 114 mg L1, close to that of the tap water (90 mg L1 TDS) collected at Virginia Tech, and lower than the requirement of potable water quality ( Naþ > Ca2þ > Mg2þ, and the anions are in the order of þ 2 Cl > NO 3 > SO4 (Vanysek, 2002). As shown in Fig. 4, Na and Cl had the highest removal rates among cations and anions, because of their large abundance and strong mobility. The removal rates of Kþ, Ca2þ, and Mg2þ were relatively low, likely related to their initial low concentrations, except that the initial concentration of Ca2þ in the brackish water A was as high as 18.6 mmol L1 (742.0 mg L1). The removal rate of NO 3 was higher than SO2 4 in the brackish waters B and C, owing to the higher mobility of NO 3 as well as the comparable concentrations of the two ions (1.1 and 0.9 mmol L1, or 65.6 and 88 mg L1 in the brackish water B, and 0.8 and 0.7 mmol L1, or 50 and 68 mg L1 in the brackish water C). The removal rate of NO 3 was considerably slow in the brackish water A, possibly related to its low concentration of 0.06 mmol L1 (or 3.5 mg L1). It was observed that a higher salt flow rate (or lower HRT) generally resulted in a higher ionic removal rate, which was consistent with overall salt removal rate discussed in the previous section. Chloride is the most common cause of toxicity in irrigation water due to its ability to accumulate in plant leaves. Leaf tissue will be severely injured if the chloride concentration exceeds the tolerance (Tak et al., 2012). At HRT of 1.7 d, the MDC decreased the chloride concentrations in brackish waters B and C to 36.3 and 14.7 mg L1, respectively, below the guidelines of “non-restriction” for sprinkler (106.5 mg L1) and surface (142 mg L1) irrigation. The desalinated brackish water
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Fig. 4 e The removal rates of major ions at three HRT (d) (A) brackish water A; (B) brackish water B; and (C) brackish water C.
A could meet the guideline only when treated with the sevenday HRT. When the HRT was shortened to 0.8 days, the chloride concentrations increased to 307.9 and 270.0 mg L1 for B and C. Cautions need to be taken because these are in the range of “slight to moderate restriction on use” of 142e350 mg L1. High sodium content in irrigation water relative to the calcium and magnesium contents, also known as sodium hazard, will cause infiltration reduction in the plant and reduce crop yield. The Sodium Adsorption Ratio (SAR) is an important parameter to access this tendency, calculated as (Miller and Gardiner, 2007): Naþ meq=L SAR ¼ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ðCaþþ meq=LÞþðMgþþ meq=LÞ 2
(16)
The SAR of the three brackish waters, treated and untreated, all oscillated between the “low sodium hazard” and “medium sodium hazard” standard of 1e18 (Fipps, 1996). The measurement of SAR together with salinity also provides the evaluation of the sodium hazard problem. With the best salinity quality at HRT of 1.7 d, treated brackish water C had SAR of 2.1 in the range of “slight to moderate restriction on use”. Desalinated brackish water B at HRT 1.7 d resulted in a high SAR of 7.5, indicating that the produced water would bring forth severe infiltration problem. If the “none-
19
restriction” of salinity is met, the SAR should always be maintained below 6 (Ayres and Westcot, 1985). Chemical amendments of the treated brackish water, such as addition of Gypsum, needs to be taken into consideration before applying the treated water to irrigation. Other inorganic ions that contribute to salinity also play important roles in plant and crop growth, such as sulfate and nitrate that benefit fertility of crops (Tak et al., 2012). At HRT of less than 2 d, the brackish water B and C both fall in the “low” to “normal” nutrient concentrations range. Brackish water A was enriched in sulfate and maintained excessive sulfate in its effluent at a short HRT. At seven-day HRT, the sulfate concentration was reduced to 33.0 mg L1 and met the “normal nutrient concentration”. The commercial ion exchange membranes usually have a pore size of 1 nm (Strathmann, 2004), and do not block molecules or ions that have a molecular weight less than 350 Da (Kim and Logan, 2013). The common inorganic ions in the 2 wastewater, Ca2þ, Mg2þ, Naþ, Kþ, NHþ 4 , SO4 , and Cl , which originally exist in brackish water as well, may not be a major concern if they move across the ion exchange membranes from wastewater into brackish water, because they will contribute to the nutrient concentrations for irrigation. When treating wastewater with high phosphate content in the anode of an MDC (which is not a case in the present study), the backdiffused phosphate will cause potential problem in irrigation process because of phosphate-related precipitation in irrigation pipe and emitters. This issue can be prevented by adjusting the pH of the desalinated water (Rauschkolb et al., 1976). Organics in wastewater exist in complex forms, and the back-diffusion of small-size organic compounds might lead to microorganism contamination of the desalinated brackish water and biofouling of the ion-exchange membranes (Ping et al., 2013). The wastewater used in this study had an initial acetate (60 Da) concentration of 0e20 mg L1 and a glucose (180 Da) concentration of ~500 mg L1. The concentrations of glucose and short chain fatty acids could increase through decomposition of large organic compounds by bacteria in the anode. The back-diffused organics during the MDC operation resulted in a TOC concentration of 2e7 mg L1 in the desalinated brackish water. We hypothesized that there could be two driving forces causing back-diffusion: the osmotic water movement from the anode to the desalination compartment, and the organics gradient between the wastewater and the brackish water. At an HRT of 1.7 d when desalinating brackish waters B and C, the osmotic pressure across the AEM dropped to 0.38, and 0.53 atm due to the lower salinity in the desalination compartment than the anode compartment (the anolyte of ~1.4 mS cm1), which meant the water moved from the desalination compartment to the anode compartment and thus water movement would not cause back-diffusion of organics. For the brackish water A, an osmotic pressure of 1.83 atm was presented between the desalination compartment (5.0 mS cm1) and anode compartment (1.4 mS cm1), and possibly organics were transported across the AEM from the anode to the desalination compartment with water as the carrier. However, the TOC in the three treated brackish waters showed undistinguishable concentrations of 6.9, 5.1, and 6.6 mg L1 for A, B, and C, respectively. Unlike seawater desalination in an MDC, in which osmotic pressure could
20
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reach as high as 10 atm, the back-diffusion of organics during desalinating brackish water was not affected by osmotic pressure severely. The organic gradient across the AEM were similar at about 70 mg L1 TOC when treating the three brackish waters, and this similar organic gradient was likely the major reason for the similar degree of organic contamination in the treated brackish waters.
4.3.
Model fitting and validation
To better understand the desalination behavior of brackish water in the MDC and to provide guidance for system operation, the MDC model was updated and implemented in MATLAB using ODE 23tb solver for solving stiff differential equations. The diffusion constant d was calibrated as 0.0096 mol L1 day1 with the steady state Csalt,m by an open circuit (OC) experiment (the performance was not subject to current generation, but only salt diffusion or water permeate) operated with the same MDC reactor fed with acetate as the substrate and salt solution of 5 g L1 NaCl. With initial salt concentration of 35 g L1 and external resistance of 0.1 U, the steady state Csalt,m and Jw along with the maximum water permeability (86 mL h1 m2 for AEM and 32 mL h1 m2 for CEM at 5 psi) provided by the manufacture (Membrane International, Inc.), were then used to estimate the water permeability of the ion exchange membranes used in this study. Fig. 5A shows the measured and simulated salt effluent conductivity in the MDC fed with acetate, and with 5 g L1 or 35 g L1 NaCl as the initial salt concentration at different external resistance loads. The two different salt concentrations were selected to represent the brackish water and seawater salinity (seawater was studied here for comparison purpose). The different external resistance loads allowed the evaluation of the model performance affected by current variation, as well as the concentration difference between different compartments which lead to salt diffusion and water permeation. At both initial salt concentrations, the salt effluent conductivity decreased as the external resistance load decreased which led to enhancement of the current generation. The rapid reduction in conductivity (with 35 g L1 as the initial salt concentration) when external resistance was changed from 100 U to 0.1 U was because of the dramatically increased current (increment of 6.7 mA), much higher than that from OC to 100 U (3.5 mA). The current change was slow with 5 g L1 as the initial salt concentration (4 mA increment for every resistance change), and so resulted in a gradual conductivity reduction. The simulated salt effluent conductivity shows strong agreement with the measured value, with SE less than 0.8% for the initial salt concentration of 35 g L1, and SE less than 2.9% for 5 g L1, except for the case of 5 g L1 NaCl operated with 0.1 U, which has a calculated SE of 14.5%. These results indicate excellent accuracy of the improved model for both high and low salinity desalination in MDC. With the improved mathematical model, the RMSE of the dynamic salt concentration from the previous MDC with dynamic anolyte flow rates was improved from 12.12% to 5.32% of their maximum values, and from 17.57% to 13.09% when changing the external resistances (Fig. S3 and S4, supplementary information) (Ping et al., 2014). For actual brackish water desalination operated with domestic wastewater in this study, the parameters related to
Fig. 5 e Experimental data and model prediction of the MDC performance: (A) synthetic NaCl solution at two different salinities with different applied external resistance; and (B) three brackish waters at different HRT. anodophilic and methanogenic miroorganisms were adopted from the previous model, and then adjusted with the experimental results obtained in this study. The maximum attainable current was estimated to be 5 mA by both the microbial growth mode in domestic wastewater and the low conductivity of wastewater (1 mS cm1) and brackish water. Given the weaker activity of anodophilic microorganisms in domestic wastewater, the parameter values of maximum substrate consumption rate by anodophilic microorganisms ks,a,max, half-saturation concentrations for the anodophillic microorganism Ka, half-saturation concentrations for the methanomaximum anodophilic genic microorganism Km, microorganism growth rate ka,max, and mediator yield YM were modified to 3.06 mg-S mg-a1 day1, 80 mg-S L1, 100 mgS L1, 0.164 d1, 2.83 mg-M mg-S1. The steady state performance at the longest HRT (the brackish water A at HRT of 6.9 d and brackish waters B&C at HRT of 1.7 d) was used to estimate model parameters (mainly transfer coefficient factor a), while other HRTs were for model validation (Fig. 5B). As discussed previously, longer HRT provided more treatment time, and thus resulted in lower effluent salt conductivity. The results showed excellent agreement between measured and simulated salt effluent conductivity (Fig. 5B), with the highest SE of 3.82% for the brackish water A, 4.96% for the brackish water B, and 10.7% for the brackish water C. The ionic composition was also well predicted by the model. Using the brackish water A as an example, its ionic composition in the desalinated effluent showed normalized RMSE of 5.21% (at HRT of 0.8 d), 15.2% (1.7 d), and 17.7% (6.9 d). The predicted concentrations of Ca2þ, Mg2þ, and SO2 4 were relatively higher than the measured values at HRTs of 6.9 d and 1.7 d, and the discrepancy might be related to the factors of pH
w a t e r r e s e a r c h 7 7 ( 2 0 1 5 ) 1 3 e2 3
and precipitation or absorption rate of hardness ions onto the membrane (Fig. 6A and B), which phenomenon was also observed in the previous study (Luo et al., 2012b). The pH of the brackish water A ranged from 7.49 to 8.51, and the higher pH in that range could accelerate the precipitation of those ions on the membrane, which was a complicated process that could not be predicted by the present model. The scaling on the ionexchange membrane probably reduced the transport ability of other ions, so that the measured Naþ concentration was higher than predicted values. However, the reason for measured Cl concentration to be lower than predicted value at HRT of 1.7 d was not clear, and it is possible the initial input Cl concentration in MATLAB was overestimated from IC result. At a shorter HRT of 0.8 d, the measured concentrations of Mg2þ and were close to the predicted values (Fig. 6C), probably SO2 4 because that the high flow rate did not allow enough time for MgSO4 to precipitate, which has a slower precipitation rate compared with CaCO3 (Ping et al., 2013). Inspired by the fact that a lower HRT in a single reactor results in a higher salt removal rate, the model simulated and compared two operational modes to identify an optimal mode for better desalination: the four-stage operation has a single feed of salt solution flowing through four MDCs in series with HRT of 1 day in each reactor, and the one-stage operation has four feed streams in parallel to four MDCs with HRT of 4 days in each reactor, respectively (Fig. 7; inset shows two operational
21
Fig. 7 e The salt concentration in the desalinated effluent in two simulated operations, four-stage, and one-stage operation, both at HRT 4 d.
modes); both systems will desalinate the same amount of salt water within the same time period. The salt concentration in the effluent decreases with the stages in the four-stage operation, while it decreases with time in the one-stage operation (Fig. 7). The four-stage operation achieves 14% improvement in salinity reduction compared with the one-stage operation. It is worth noting that more stages could exhibit better improvement, but not intensively. For example, a simulated ten-stage operation further improves the desalination by another 4%, compared with the four-stage operation. The model assumes same microorganism population and growth mode in the four reactors of both operations; however, actual application of the staging operation might result in different microorganism activities in different reactors. For example, the earlier stage will most likely have stronger anodophilic activities, because of sufficient uptake of electrons. Thus, the identified optimal operation mode will also need to be experimentally verified.
5.
Conclusions
This study has demonstrated the effective desalination of brackish water and treatment of municipal wastewater in MDCs, through integrated experiments and mathematical modeling. Given sufficient HRT, the desalinated brackish water could meet the none-restriction irrigation standard in terms of both salinity and composition of individual ions. A small amount of back diffused organics might lead to microbial contamination of the desalinated water, and postdisinfection may be required to inhibit bacteria growth. The improved mathematical model fit the experimental data fairly well, and was able to provide useful information for operation optimization. Those results encourage further investigation and development of MDC technology for combined wastewater and brackish water treatment.
Acknowledgments Fig. 6 e Experimental data and model prediction of the concentration of major ions in the desalinated brackish water A at HRT (A) 6.9 d; (B) 1.7 d, and (C) 0.8 d.
This project was financially supported by Research Grant Award No. US-4455-11 from BARD, the United States-Israel
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Binational Agricultural Research and Development Fund. The authors would like to thank Dr. Raphael Semiat (Technion) for providing the compositions of three brackish waters.
Appendix A. Supplementary data Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.watres.2015.03.008.
references
Ayres, R.S., Westcot, D.W., 1985. Water Quality for Agriculture. FAO Irrigation & Drainage Paper, 29. Food and Agriculture Organization of the United Nations, Rome. Brastad, K.S., He, Z., 2013. Water softening using microbial desalination cell technology. Desalination 309, 32e37. Cao, X.X., Huang, X., Liang, P., Xiao, K., Zhou, Y.J., Zhang, X.Y., Logan, B.E., 2009. A new method for water desalination using microbial desalination cells. Environ. Sci. Technol. 43 (18), 7148e7152. Chen, X., Xia, X., Liang, P., Cao, X., Sun, H., Huang, X., 2011. Stacked microbial desalination cells to enhance water desalination efficiency. Environ. Sci. Technol. 45, 2465e2470. Chen, X., Liang, P., Wei, Z., Zhang, X., Huang, X., 2012. Sustainable water desalination and electricity generation in a separator coupled stacked microbial desalination cell with buffer free electrolyte circulation. Bioresour. Technol. 119, 88e93. Fipps, G., 1996. Irrigation Water Quality Standards and Salinity Management Strategies, seventh ed. Texas Agricultural Extension Service, Texas A & M University System. Ge, Z., Dosoretz, C., He, Z., 2014. Effects of numbers of cell pairs on the performance of microbial desalination cells. Bioresour. Technol. 341, 101e106. Jacobson, K.S., Drew, D.M., He, Z., 2010. Efficient salt removal in a continuously operated upflow microbial desalination cell with an air cathode. Bioresour. Technol. 102, 376e380. Jacobson, K.S., Drew, D.M., He, Z., 2011. Use of a liter-scale microbial desalination cell as a platform to study bioelectrochemical desalination with salt solution or artificial seawater. Environ. Sci. Technol. 45, 4652e4657. Kim, Y., Logan, B.E., 2011. Series assembly of microbial desalination cells containing stacked electrodialysis cells for partial or complete seawater desalination. Environ. Sci. Technol. 45 (13), 5840e5845. Kim, Y., Logan, B.E., 2013. Microbial desalination cells for energy production and desalination. Desalination 308, 122e130. Lee, H.S., Parameswaran, P., Marcus, A.K., Torres, C.I., Rittmann, B.E., 2008. Evaluation of energy-conversion efficiencies in microbial fuel cells (MFCs) utilizing fermentable and non-fermentable substrates. Water Res. 42, 1501e1510. atsah ha-le umit le-mehkar ule-fituah, 1972. Levite, G.A., Mo Utilization of brackish water. In: Proceeding of the Ninth Israel Symposium on Desalination, Bitan Aharon. Jerusalem. National Council for Research and Development, Prime Minister's Office, Jerusalem, Israel. Luo, H.P., Xu, P., Roane, T.M., Jenkins, P.E., Ren, Z.Y., 2012a. Microbial desalination cells for improved performance in wastewater treatment, electricity production, and desalination. Bioresour. Technol. 105, 60e66. Luo, H.P., Xu, P., Jenkins, P.E., Ren, Z.Y., 2012b. Ionic composition and transport mechanisms in microbial desalination cells. J. Membr. Sci. 409, 16e23.
Luo, H.P., Xu, P., Ren, Z.Y., 2012c. Long-term performance and characterization of microbial desalination cells in treating domestic wastewater. Bioresour. Technol. 120, 187e193. Marcus, A.K., Torres, C.I., Rittmann, B.E., 2007. Conduction-based modeling of the biofilm anode of a microbial fuel cell. Biotechnol. Bioeng. 98 (6), 1171e1182. Miller, R.W., Gardiner, D.T., 2007. Soils in Our Environment, ninth ed. Prentice Hall-Inc, Upper Sddle River, New Jersey. National Research Council, 2008. Desalination: a National Perspective. National Academies Press, Washington, D.C. Ping, Q., He, Z., 2013. Improving the flexibility of microbial desalination cells through spatially decoupling anode and cathode. Bioresour. Technol. 144, 304e310. Ping, Q., Cohen, B., Dosoretz, C., He, Z., 2013. Long-term investigation of fouling of cation and anion exchange membranes in microbial desalination cells. Desalination 325, 48e55. Ping, Q., Zhang, C., Chen, X., Zhang, B., Huang, Z., He, Z., 2014. A mathematical model of dynamic behavior of microbial desalination cells for simultaneous wastewater treatment and water desalination. Environ. Sci. Technol. 48, 13010e13019. Qu, Y., Feng, Y., Wang, X., Liu, J., Lv, J., He, W., Logan, B.E., 2012. Simultaneous water desalination and electricity generation in a microbial desalination cell with electrolyte recirculation for pH control. Bioresour. Technol. 106, 89e94. Rhoads, J.D., Kandiah, A., Maghali, A.M., 1992. The Use of Saline Waters for Crop Production. FAO Irrigation & Drainage Paper, 48. Food and Agriculture Organization of the United Nations, Rome. Rauschkolb, R.S., Rolston, D.E., Miller, R.J., Carlton, A.B., Burau, R.G., 1976. Applying phosphorus through drip system. Calif. Agric. 8e10. Strathmann, H., 2004. Ion-exchange Membrane Separation Processes. Elsevier B.V, Amsterdam. Tak, H.I., Bakhtiyar, Y., Ahmad, F., Inam, A., 2012. Effluent quality parameters for safe use in agriculture. In: Lee, Teang Shui (Ed.), Water Quality, Soil and Managing Irrigation of Crops. InTech. USBR (U.S. Bureau of Reclamation), 2003. Desalting Handbook for Planners, third ed. USBR, Washington, D.C. Vanysek, P., 2002. Ionic conductivity and diffusion at infinite dilution. In: CRC Handbook of Chemistry and Physics, 83rd ed. CRC Press, Boca Raton. Walker, W.S., Kim, Y., Lawler, D.F., 2014. Treatment of model inland brackish groundwater reverse osmosis concentrate with electrodialysis e part II: sensitivity to voltage application and membranes. Desalinatoin 345, 128e135. Zhang, B., He, Z., 2012. Energy production, use and saving in a bioelectrochemical desalination system. RSC Adv. 2, 10673e10679. Zhang, F., He, Z., 2015. Scaling up microbial desalination cell with a post-aerobic treatment process for simultaneous wastewater treatment and seawater desalination. Desalination 360, 28e34. Zuo, K., Yuan, L., Wei, J., Liang, P., Huang, X., 2013. Competitive migration behaviors of multiple ions and their impacts on ionexchange resin packed microbial desalination cell. Bioresour. Technol. 146, 637e642.
Glossary a: Current efficiency aion,a: Ionic activity in the anode compartment aion,c: Ionic activity in the cathode compartment aion,m: Ionic activity in the desalination compartment AAEM: Water permeability of AEM ACEM: Water permeability of CEM Cion,in: Individual ion concentration in the salt influent
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Cion,m: Individual ion concentration in the desalination compartment Csalt,a: Salt concentration in the anode compartment Csalt,a,in: Salt concentration in the anolyte influent Csalt,c: Salt concentration in the cathode compartment Csalt,in: Salt concentration in the salt influent Csalt,m: Salt concentration in the desalination compartment d: The membrane salt transfer coefficient Danode: The dilution rates in the anode compartment Dsalt: The dilution rates in the desalination compartment F: Faraday constant i: Van't Hoff factor Ia¼1: The current when a ¼ 1 Ira,max: The current when da/dI is the greatest IMDC: Current generated by MDC Jw,a: Water flux between the desalination and anode compartment Jw,c: Water flux between the desalination and cathode compartment
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OPconc: Concentration overpotential Qanode: Flow rate of the anolyte in the anode compartment Qsalt: Flow rate of the salt solution in the desalination compartment R: Ideal gas constant Rext: External resistance Rint: Internal resistance of MDC T: MDC temperature tAEM,ion: Transport number in AEM tCEM,ion: Transport number in CEM u: Mobility of ions in solution Vanode: The volume of anode compartment Vcathode: The volume of cathode compartment Vsalt: The volume of desalination compartment Vjct: Junction potential VOC: Open circuit cell voltage that depends on the anodophilic microorganism concentration zion: Ionic charge
Available online at www.sciencedirect.com
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Integrated experimental investigation and mathematical modeling of brackish water desalination and wastewater treatment in microbial desalination cells Qingyun Ping a, Zuyi Huang b, Carlos Dosoretz c, Zhen He a,* a
Department of Civil and Environmental Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA b Department of Chemical Engineering, Villanova University, Villanova, PA 19085, USA c Faculty of Civil and Environmental Engineering, Technion-Israel Institute of Technology, Haifa 32000, Israel
article info
abstract
Article history:
Desalination of brackish water can provide freshwater for potable use or non potable ap-
Received 10 December 2014
plications such as agricultural irrigation. Brackish water desalination is especially attrac-
Received in revised form
tive to microbial desalination cells (MDCs) because of its low salinity, but this has not been
8 March 2015
well studied before. Herein, three brackish waters prepared according to the compositions
Accepted 10 March 2015
of actual brackish water in three locations in Israel were examined with domestic waste-
Available online 20 March 2015
water as an electron source in a bench-scale MDC. All three brackish waters could be effectively desalinated with simultaneous wastewater treatment. The MDC achieved the
Keywords:
highest salt removal rate of 1.2 g L1 d1 with an initial salinity of 5.9 g L1 and a hydraulic
Microbial desalination cells
retention time (HRT) of 0.8 d. The desalinated brackish water could meet the irrigation
Microbial fuel cells
standard of both salinity (450 mg L1 TDS) and the concentrations of major ionic species,
Brackish water
given a sufficient HRT. The MDC also accomplished nearly 70% removal of organic com-
Wastewater
pounds in wastewater with Coulombic efficiency varied between 5 and 10%. A previously
Mathematical model
developed MDC model was improved for brackish water desalination, and could well predict salinity variation and the concentrations of individual ions. The model also simulated a staged operation mode with improved desalination performance. This integrated experiment and mathematical modeling approach provides an effective method to understand the key factors in brackish water desalination by MDCs towards further system development. © 2015 Elsevier Ltd. All rights reserved.
1.
Introduction
Because of the world-wide water shortage and local water scarcity, desalination has been increasingly considered as a * Corresponding author. Tel.: þ1 540 231 1346; fax: þ1 540 231 7698. E-mail address: [email protected] (Z. He). http://dx.doi.org/10.1016/j.watres.2015.03.008 0043-1354/© 2015 Elsevier Ltd. All rights reserved.
viable approach for freshwater supply (National Research Council, 2008). The recently emerged microbial desalination cell (MDC) appears to be a promising alternative or supplement for traditional desalination technologies. An MDC
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converts the energy stored in wastewater directly into electricity by microorganisms and utilizes it in situ to drive desalination in a process similar to electrodialysis (ED) (Cao et al., 2009). The difference between MDC and ED is the source of electrons and energy consumption: an MDC uses the electrons released by microbial oxidation of organic compounds, while an ED is driven by electrons from water oxidation; as a result, an MDC does not necessarily require external voltage, but an ED must be applied with a high external voltage or current. The MDC has been advanced with reactor configurations, such as stacked reactor (Kim and Logan, 2011; Chen et al., 2011; Ge et al., 2014), decoupled reactor (Ping and He, 2013), and upflow tubular reactor that has demonstrated a salt removal efficiency >99% (Jacobson et al., 2010, 2011). Optimized operation through recirculation between the anode and the cathode compartments could achieve pH balance without the addition of costly buffer (Chen et al., 2012; Qu et al., 2012). Fundamental studies have also been conducted to reveal the diverse microbial community in the anode of MDC (Luo et al., 2012a). Recently, MDCs have been scaled up to a total liquid volume of 105 L, which encourages further development of this technology (Zhang and He, 2015). Although MDCs can achieve desalination without external voltage applied, its desalination requires a fairly long time because of slow microbial oxidation, compared with electrochemical oxidation of water in ED. The low desalination rate of MDCs indicates that this technology may be more suitable for application as a pre-desalination process for conventional desalination such as RO (reverse osmosis) or ED (Zhang and He, 2012). Another potential application of MDC technology is to desalinate low-salinity water, such as brackish water that has TDS (total dissolved solids) in the range of 1000 to atsah, 1972), or the treated waste10,000 ppm (Levite and Mo water. In many arid parts of the world, the local aquifers that contain brackish water are the main source of freshwater. It is of great importance to desalinate brackish water for municipal or agricultural applications. ED and EDR (electrodialysis reversal) are the current technologies for treating brackish water with TDS up to 3500 mg L1; a higher salinity significantly increases the energy consumption compared with RO (USBR, 2003). The salinity in brackish water comes from two sources: dissolution of minerals, and natural mixing of seawater with groundwater in coastal aquifers (National Research Council, 2008). Most brackish water cannot be directly used for drinking purpose or irrigation due to the high salinity, and specific ion toxicity for plants or the possibility of deteriorating soil conditions (Rhoads et al., 1992). There have been several MDC studies that examined desalination of synthetic salt solution with salinity similar to brackish water (Luo et al., 2012c; Zuo et al., 2013). The study of actual brackish water was reported only in a previous work that focused on the softening of hardness in several groundwater samples (Brastad and He, 2013). The transport behavior of multiple ions across ion-exchange membranes were studied at the same initial molar concentration with only one kind of counter ion (anion/cation) (Luo et al., 2012b); however the results cannot be applied to predict the ion composition in the actual brackish water desalination where the individual ion has different concentration. The transport rate of individual ions is a product of mobility (affected by hydrated radius and ionic
charge) and ion concentration (Strathmann, 2004), while the previous study only considered hydrated radius as influencer. Clearly, there is a lack of detailed analysis and understanding of removal of different ionic species during desalinating actual brackish water or saline water with more complicated composition than NaCl solution in MDCs. To assist the interpretation of the data obtained from the bench studies and to provide guidance for system operation, mathematical models of MDCs treating brackish water will be very valuable. Recently, the first MDC model was reported and it could effectively predict MDC performance under different operating conditions (Ping et al., 2014). However, the model did not well predict the change in salt concentration, likely related to that the low current efficiency, which mostly occurs when maximum current is not reached, was neglected in the model development. Desalinating brackish water in an MDC by using the energy obtained from domestic wastewater comes with two issues: low organic strength in the anode compartment, and low salinity in the desalination compartment, both of which will lead to current deviating from normal values and the low current efficiency due to low current generation. In addition, diffusion element in the previous model might not work for brackish water considering the difference in salt concentration across ion exchange membranes. Therefore, the previously developed MDC model must be improved with new information obtained from brackish water desalination. In this study, we have adopted an integrated approach of experimental investigation and mathematical modeling to study brackish water desalination in bench scale MDCs. Three synthetic brackish waters were prepared with the recipes to mimic actual brackish water in three locations in Israel. Actual domestic wastewater (primary effluent) was used as an anode substrate to provide driving force for desalination. The objectives of this study were: (1) to demonstrate the MDC performance treating brackish water and actual wastewater; (2) to understand the removal of different ionic species during desalination; and (3) to improve the MDC model for brackish water desalination by incorporating junction potential, current efficiency, restricted diffusion, and osmotic flux. The model was calibrated with steady state values and validated by experimental data of both dynamic and steady state conditions.
2.
Materials and methods
2.1.
MDC setup and operation
The MDC was constructed as a tubular reactor similarly to the one in the previous study (Ping et al., 2014), consisting of two layers of ion exchange membranes (IEM): anion exchange membrane (AEM, AMI-7001, Membrane International, Inc., Glen Rock, NJ, USA) with a 3.8-cm diameter and 20-cm length formed the anode compartment (300 mL), and cation exchange membrane (CEM, CMI-7000, Membrane International, Inc.) that had a diameter of 5 cm and a length of 20 cm wrapped the AEM tube and created a space between the two membrane tubes forming a desalination compartment (150 mL) (Fig. S1, supplementary information). The distance
w a t e r r e s e a r c h 7 7 ( 2 0 1 5 ) 1 3 e2 3
between the AEM and the CEM was 0.6 cm. The anode electrode was a 20-cm long carbon fiber brush, and the cathode electrode was a piece of carbon cloth coated with activated carbon supported platinum (Pt/C) as a catalyst at a loading rate of 0.2 mg Pt cm2. An external resistor of 0.1 U connected the two electrodes by using titanium wire. The anode feed solution was the primary effluent from a local wastewater treatment plant (Peppers Ferry, Radford, VA, USA), and amended with 500 mg L1 of glucose. The modified wastewater contained a COD (chemical oxygen demand) concentration varying between 500 and 650 mg L1. Three brackish waters were prepared by dissolving different salt compounds into tap water according to the composition shown in Table 1. The catholyte was prepared same as the brackish water used in the desalination compartment, dripping from the top to the bottom of the outer (CEM) tube for rinsing the cathode electrode and recirculated from a 9-L reservoir at a recirculation rate of 35 mL min1. The anolyte had a feeding rate of 0.5 mL min1, resulting in a hydraulic retention time (HRT) of 10 h, and was recirculated at 100 mL min1. The brackish water was fed into the desalination compartment without recirculation at three flow rates, 0.015 mL min1 (HRT of 6.9 d), 0.06 mL min1 (HRT of 1.7 d), and 0.13 mL min1 (HRT of 0.8 d) for the brackish water A, or 0.06 mL min1 (HRT of 1.7 d), 0.13 mL min1 (HRT of 0.8 d), and 0.3 mL min1 (HRT of 0.35 d) for the brackish waters B & C.
2.2.
Measurement and analysis
The MDC voltage was recorded every 3 min using a digital multimeter (Keithley Instruments, Inc., Cleveland, OH, USA). The conductivity of the salt solution was measured using a benchtop conductivity meter (Mettler-Toledo, Columbus, OH, USA). The chemical oxygen demand (COD) was measured using a colorimeter according to the manufacture manual (Hach Company, Loveland, CO USA). The ion compositions in the solution were measured using ion chromatography (Dionex DX-500) with suppressed conductivity detection. The column used for cations was a CS-16 with a CSRS-300 suppressor and for anions was an AS-9HC with an ASRS-300 suppressor. The TOC (total organic carbon) of the samples was measured by Shimadzu Scientific Instruments TOC-VCP with combustion catalytic oxidation/NDIR detection method. The salt removal rate was calculated as the removed salt concentration divided by HRT.
Table 1 e The concentrations of major ions (mg L¡1) in three brackish waters. Brackish water composition Ca2þ Mg2þ Naþ Kþ NHþ 4 HCO 3 SO2 4 Cl NO 3 TDS
A
B
C
742 207 1054 26 0.0 92 781 2942 3.5 5887.7
105 78 364.5 5.3 0.0 405 88 620.3 65.6 1540
71.7 56.1 235 3.7 0.0 369.4 68 366 50 1068
3.
Model improvement
3.1.
Electricity generation
15
Junction potential created by concentration gradient across the IEM is an additional potential source responsible for the ion-separation besides the potential difference created by electrode reactions. In an MDC treating wastewater and seawater, the junction potential is up to 0.2 V. For brackish water desalination, when the salt concentration in the desalination compartment is reduced lower than in the anolyte or catholyte, the junction potential poses a negative effect on the current generation, In this updated model, the junction potential is defined as (Kim and Logan, 2013): Vjct ¼
RT X tAEM;ion aion;m RT X tCEM;ion aion;m ln ln þ F ion zion F ion zion aion;a aion;c
(1)
where tAEM,ion and tCEM,ion are the transport number of ionic species in AEM and CEM, zion is the ionic charge, aion,m, aion,a, and aion,c are the ionic activity in the desalination, anode, and cathode compartments, F is the Faraday constant (96,485 A s mol1), R is the ideal gas constant (8.31 J K1 mol1), and T is the MDC temperature (298.15 K). In an MDC, the junction potential can be roughly estimated by assuming that the activity ratio equals the total dissolved solids ratio. The ideal tNaþ and tCl will be 0 and 1 for AEM, and 1 and 0 for CEM. The MDC current is then calculated as: IMDC ¼
VOC OPconc þ Vjct ðRext þ Rint Þ
(2)
where VOC is the open circuit cell voltage that depends on the anodophilic microorganism concentration, OPconc is the concentration overpotential and Rint is the internal resistance of the MDC, which were defined in the previous study (Ping et al., 2014). Rext is the applied external resistance.
3.2.
Mass balance of salt in MDCs
To better show the removal of individual ions in brackish water, the present model takes milliequivalent ions per liter (meq L1 ¼ mg L1 / equivalent weight) as the unit for salt concentration instead of mol L1 in the previous model. We incorporate in the present model the current efficiency a, which shows the ratio between the coulombs harvested from the movement of salt ions and the coulombs harvested from electrical circuit. The ideal situation is that one mole of electrons would take away two molar-equivalents of ions, which means that a is equal to 1. However, it was observed in our previous study that an MDC usually exhibits low current efficiency when the maximum current is not reached. Thus, we proposed an inverse tangent function to present the relationship between current and a. a begins with a zero value, increases sharply, and levels off upon the increase of IMDC from zero. The small value of a for a low IMDC is able to relax the assumption made in the previous model in which a was always equal to 1. a¼
arctanðIMDC *1000 Ira;max *1000Þ þ arctanðIra;max *1000Þ arctanðIa¼1 *1000 Ira;max *1000Þ þ arctanðIra;max *1000Þ
(3)
16
w a t e r r e s e a r c h 7 7 ( 2 0 1 5 ) 1 3 e2 3
where IMDC is the current generated by the MDC, Ira,max is the current when da/dI is the greatest and needs to be estimated from experimental data, and Ia¼1 is the current when a ¼ 1. A profile of a is shown in Fig. S2A. The water transport across an IEM is another important factor that contributes to the reduced salt concentration in the desalination compartment. The water flux between the desalination compartment and the anode and cathode compartments is represented by an osmotic pressure model, and the osmotic pressures in the solutions were calculated in accordance with the Van't Hoff's equation: Jw;a ¼ AAEM $RTiðCsalt;m Csalt;a Þ 2
(4)
Jw;c ¼ ACEM $RTiðCsalt;m Csalt;c Þ 2
(5)
where, Csalt,m, Csalt,a, and Csalt,c are the salt concentrations in the desalination, anode, and cathode compartments (meq L1), respectively. AAEM and ACEM stand for the water permeability of anion and cation exchange membranes (L day1 atm1), respectively. i is the Van't Hoff factor that reflects the number of discrete ions when compounds dissolve in water and was approximated to be 2 for salt NaCl in the present study. Diffusion of salt molecules from high concentration to low concentration is greatly smaller in the opposite direction of current-driven ion movement and does not follow a linear relationship of the salt concentration difference as defined by the previous model. Therefore, to make concentration difference less influential when the salt concentration in the desalination compartment is less than in the anode or cathode compartment, the diffusion was modified to restricted diffusion functions Dres,a and Dres,c by an inverse tangent function. The profile of diffusion is shown in Fig. S2B.
where Qsalt and Qanode are the flow rates (L day1) of the salt solution in desalination compartment and of anolyte in the anode compartment. Vsalt, Vanode, and Vcathode are the volumes of the desalination, anode, and cathode compartments. Csalt,in and Csalt,a,in are the salt concentration in the salt influent and anolyte influent (meq L1). Dsalt and Danode are the dilution rates (day1) in the desalination compartment and anode compartment defined in the previous model quantified by the ratio of the flow rate over the volume of the compartment. d is the membrane salt transfer ability (g L1 day1). The first and second terms of Equations (8) and (9) represent the cause of concentration change by inflow and outflow of solutions. The third term in Equations (8) and (9), and the first term in Equation (10) represent the current-driven movement of ions. The last two terms in Equation (8) and the last terms in Equations (9) and (10) show the diffusion between the three compartments. The volume ratios of desalination compartment to anode or cathode compartment were considered for the rate change of Csalt,a, and Csalt,c. To show the individual ion concentration in the salt solu2 tion, such as Naþ, Kþ, Mg2þ, Ca2þ, Cl, NO 3 , SO4 , the following equations are needed. dCion;m Qsalt þ Jw;a þ Jw;c ¼ Dsalt $Cion;in $Cion;m dt Vsalt IMDC 4ion $ $a þ d$Dres;a þ d$Dres;c F$Vsalt
where Cion,in, and Cion,m are the individual ion concentration in the salt influent and desalination compartment, and ion refers to any anion or cation according to the ion composition in the salt influent. 4ion is the ratio defined as
Dres;a ¼ ½arctanððCsalt;m Csalt;a Þ 2,50 piÞ þ arctanðpiÞ
(6)
u$Canion;m 4anion ¼ P u$Canion;m
Dres;c ¼ ½arctanððCsalt;m Csalt;c Þ 2,50 piÞ þ arctanðpiÞ
(7)
or
The previous model assumed that only NaCl will cause concentration-gradient-driven-diffusion of salt, and excluded the contribution of current-driven movement of ions to the salt concentration change in the anode and cathode compartments. In the case of brackish water desalination, where the concentration difference could be very small and even negative, it causes large discrepancy from the experimental data. Concerning the above facts, the updated equations for concentration change in the desalination compartment, the anode, and the cathode compartments were modified as Equations (8)e(10): dCsalt;m Qsalt þ Jw;a þ Jw;c IMDC ¼ Dsalt $Csalt;in $Csalt;m 2$ $a dt Vsalt F$Vsalt 2d$Dres;a 2d$Dres;c
Qanode Jw;a dCsalt;a IMDC ¼ Danode $Csalt;a;in $Csalt;a þ 2$ $a Vanode dt F$Vanode Vsalt þ 2d$Dres;a $ Vanode dCsalt;c IMDC Vsalt ¼ 2$ $a þ 2d$Dres;c $ dt F$Vcathode Vcathode
u$Ccation;m 4cation ¼ P u$Ccation;m
dCsalt;m X dCion;m ¼ dt dt
(12b)
(13)
Parameter estimation
Parameter estimation was performed with fmincon subroutine in Matlab to search a local minimum of objective function defined as normalized room-mean-square-error (RMSE) for dynamic data:
(9)
rffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 PN yi b yi i¼1 RMSE ¼
(10)
(12a)
where u is the mobility of ions in solution (Vanysek, 2002). Equation (8) is then modified to Equation (13) by summing up the individual ion concentration in the salt solution acP cording to the relationship Cion,m ¼ Csalt,m, and P Cion,in ¼ Csalt,in.
3.3. (8)
(11)
N
bÞ maxð y
Or squared error (SE) for steady sate data:
(14)
w a t e r r e s e a r c h 7 7 ( 2 0 1 5 ) 1 3 e2 3
SE ¼
sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi bi 2 yi y b y
17
(15)
^i and yi represent experimental data and model prewhere y dicted values at tj or at steady state. Constraints were set to satisfy the true yield range for anodophilic microorganisms between 0.027 and 0.054 mg-Biomass mg-COD1 (Marcus et al., 2007).
4.
Results and discussion
4.1.
Wastewater treatment
The MDC effectively treated wastewater with little influence from the different salinity of brackish waters or current generation. With the initial COD concentration of 500e650 mg L1 (varied due to variation of organic concentration in actual wastewater), the MDC removed the COD of 421 ± 85 mg L1, resulting in a final COD concentration of 80e262 mg L1 and the COD removal rate of 68.9 ± 10.7%. Current generation was affected by the salinity (or conductivity) of the brackish water. The MDC generated 12.3 ± 2.4 A m3 when treating the brackish water A, which had the highest initial salinity of 5.9 g L1 of TDS among the three brackish waters. Consequently, higher Coulombic efficiency (of 10.9 ± 0.9%) was observed with the brackish water A. For comparison, the brackish waters B (1.5 g TDS L1) and C (1.1 g TDS L1) resulted in lower current generation of 8.1 ± 0.5 A m3 and 7.5 ± 1.0 A m3, respectively; they also had lower Coulombic efficiency of 5.7 ± 0.6% and 5.6 ± 1.2%, respectively (Fig. 1). The lower Coulombic efficiency with treating the brackish waters B and C, along with similar COD removal performance (to that with the brackish water A) indicated that, with decreased conductivity in the desalination compartment, the portion of COD used for electricity generation also decreased. Nonanodophilic microorganism played an important role in removing COD, especially when the current generation was suppressed, thereby maintaining a comparable COD concentration in the final effluent. When the initial organic strength in wastewater was increased to ~1162 mg L1 by adding more glucose for desalinating the brackish water A, the current was not improved. In fact, it was observed that the increased COD strength lowered Coulombic efficiency to 5.8% (Fig. 1) and resulted in a higher effluent COD of 524 mg L1. Those results suggest that the present MDC system was not limited by the anode activity and electron source; instead, the limiting factors that resulted in low CE might come from the low conductivity in both the wastewater and the desalination compartment, and complex substrates that led to competing electron sinks (Lee et al., 2008).
4.2.
Brackish water desalination
4.2.1.
General desalination performance
The MDC accomplished desalination of the tested brackish waters, affected by both salinity and HRT of brackish water. At the same HRT of 0.8 d (salt flow rate of 0.13 mL min1), the MDC decreased the conductivity by 19.6% in the brackish water A, while the conductivity reduction in the brackish
Fig. 1 e Coulombic efficiency of the MDC at different current densities when desalinating three types of brackish waters.
waters B and C was much higher at 43.4 and 57.4%, respectively (Fig. 2A). Increasing the HRT to 1.7 d (salt flow rate of 0.06 mL min1) significantly improved the conductivity reduction to 33.3 ± 7.2% for the brackish water A; meanwhile, the MDC further improved the desalination of the brackish waters B and C to 82.5 ± 5.0 and 88.1 ± 0.9%, respectively. To achieve desalination of >90% for the brackish water A, the HRT must be increased to 7 d. It was observed that higher desalination efficiency was obtained at a longer HRT and the trend became more distinct as the initial salinity decreased (Fig. 2A), suggesting that the treatment time had a greater influence on desalination because of the limited desalination capacity of the present MDC. Salt removal rate, on the other hand, exhibited a different trend from desalination efficiency (or conductivity decrease) (Fig. 2B). At the HRT of 0.8 or 1.7 d, the salt removal rate increased for brackish waters C, B, and A (0.75, 0.80, and 1.2 g L1 day1; or 0.52, 0.74, and 1.1 g L1 day1) as the initial salinity increased (C < B < A). Relatively higher salt removal rate was also observed with a shorter HRT (Fig. 2B). The accelerated desalination with higher initial salinity or shorter HRT was because of the resulted higher conductivity in the desalination compartment (as well as the salt effluent) that led to a lower internal resistance and thus higher current generation that drove desalination. The slightly lower salt removal rate of treating brackish water C at HRT of 0.35 d than that at 0.8 d was likely due to the low current of 6.4 A m3 compared with 7.5 A m3. The higher conductivity of 1.2 mS cm1 (0.35 d) compared with 0.7 mS cm1 (0.8 d) did not lead to higher current generation, indicating that some factors other than electrolyte conductivity (resistance) limited the MDC performance. Given sufficient retention time, the MDC could reduce the salinity to a very low level. For example, at the HRT of 1.7 d, the TDS of the brackish water C was decreased to 114 mg L1, close to that of the tap water (90 mg L1 TDS) collected at Virginia Tech, and lower than the requirement of potable water quality ( Naþ > Ca2þ > Mg2þ, and the anions are in the order of þ 2 Cl > NO 3 > SO4 (Vanysek, 2002). As shown in Fig. 4, Na and Cl had the highest removal rates among cations and anions, because of their large abundance and strong mobility. The removal rates of Kþ, Ca2þ, and Mg2þ were relatively low, likely related to their initial low concentrations, except that the initial concentration of Ca2þ in the brackish water A was as high as 18.6 mmol L1 (742.0 mg L1). The removal rate of NO 3 was higher than SO2 4 in the brackish waters B and C, owing to the higher mobility of NO 3 as well as the comparable concentrations of the two ions (1.1 and 0.9 mmol L1, or 65.6 and 88 mg L1 in the brackish water B, and 0.8 and 0.7 mmol L1, or 50 and 68 mg L1 in the brackish water C). The removal rate of NO 3 was considerably slow in the brackish water A, possibly related to its low concentration of 0.06 mmol L1 (or 3.5 mg L1). It was observed that a higher salt flow rate (or lower HRT) generally resulted in a higher ionic removal rate, which was consistent with overall salt removal rate discussed in the previous section. Chloride is the most common cause of toxicity in irrigation water due to its ability to accumulate in plant leaves. Leaf tissue will be severely injured if the chloride concentration exceeds the tolerance (Tak et al., 2012). At HRT of 1.7 d, the MDC decreased the chloride concentrations in brackish waters B and C to 36.3 and 14.7 mg L1, respectively, below the guidelines of “non-restriction” for sprinkler (106.5 mg L1) and surface (142 mg L1) irrigation. The desalinated brackish water
w a t e r r e s e a r c h 7 7 ( 2 0 1 5 ) 1 3 e2 3
Fig. 4 e The removal rates of major ions at three HRT (d) (A) brackish water A; (B) brackish water B; and (C) brackish water C.
A could meet the guideline only when treated with the sevenday HRT. When the HRT was shortened to 0.8 days, the chloride concentrations increased to 307.9 and 270.0 mg L1 for B and C. Cautions need to be taken because these are in the range of “slight to moderate restriction on use” of 142e350 mg L1. High sodium content in irrigation water relative to the calcium and magnesium contents, also known as sodium hazard, will cause infiltration reduction in the plant and reduce crop yield. The Sodium Adsorption Ratio (SAR) is an important parameter to access this tendency, calculated as (Miller and Gardiner, 2007): Naþ meq=L SAR ¼ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ðCaþþ meq=LÞþðMgþþ meq=LÞ 2
(16)
The SAR of the three brackish waters, treated and untreated, all oscillated between the “low sodium hazard” and “medium sodium hazard” standard of 1e18 (Fipps, 1996). The measurement of SAR together with salinity also provides the evaluation of the sodium hazard problem. With the best salinity quality at HRT of 1.7 d, treated brackish water C had SAR of 2.1 in the range of “slight to moderate restriction on use”. Desalinated brackish water B at HRT 1.7 d resulted in a high SAR of 7.5, indicating that the produced water would bring forth severe infiltration problem. If the “none-
19
restriction” of salinity is met, the SAR should always be maintained below 6 (Ayres and Westcot, 1985). Chemical amendments of the treated brackish water, such as addition of Gypsum, needs to be taken into consideration before applying the treated water to irrigation. Other inorganic ions that contribute to salinity also play important roles in plant and crop growth, such as sulfate and nitrate that benefit fertility of crops (Tak et al., 2012). At HRT of less than 2 d, the brackish water B and C both fall in the “low” to “normal” nutrient concentrations range. Brackish water A was enriched in sulfate and maintained excessive sulfate in its effluent at a short HRT. At seven-day HRT, the sulfate concentration was reduced to 33.0 mg L1 and met the “normal nutrient concentration”. The commercial ion exchange membranes usually have a pore size of 1 nm (Strathmann, 2004), and do not block molecules or ions that have a molecular weight less than 350 Da (Kim and Logan, 2013). The common inorganic ions in the 2 wastewater, Ca2þ, Mg2þ, Naþ, Kþ, NHþ 4 , SO4 , and Cl , which originally exist in brackish water as well, may not be a major concern if they move across the ion exchange membranes from wastewater into brackish water, because they will contribute to the nutrient concentrations for irrigation. When treating wastewater with high phosphate content in the anode of an MDC (which is not a case in the present study), the backdiffused phosphate will cause potential problem in irrigation process because of phosphate-related precipitation in irrigation pipe and emitters. This issue can be prevented by adjusting the pH of the desalinated water (Rauschkolb et al., 1976). Organics in wastewater exist in complex forms, and the back-diffusion of small-size organic compounds might lead to microorganism contamination of the desalinated brackish water and biofouling of the ion-exchange membranes (Ping et al., 2013). The wastewater used in this study had an initial acetate (60 Da) concentration of 0e20 mg L1 and a glucose (180 Da) concentration of ~500 mg L1. The concentrations of glucose and short chain fatty acids could increase through decomposition of large organic compounds by bacteria in the anode. The back-diffused organics during the MDC operation resulted in a TOC concentration of 2e7 mg L1 in the desalinated brackish water. We hypothesized that there could be two driving forces causing back-diffusion: the osmotic water movement from the anode to the desalination compartment, and the organics gradient between the wastewater and the brackish water. At an HRT of 1.7 d when desalinating brackish waters B and C, the osmotic pressure across the AEM dropped to 0.38, and 0.53 atm due to the lower salinity in the desalination compartment than the anode compartment (the anolyte of ~1.4 mS cm1), which meant the water moved from the desalination compartment to the anode compartment and thus water movement would not cause back-diffusion of organics. For the brackish water A, an osmotic pressure of 1.83 atm was presented between the desalination compartment (5.0 mS cm1) and anode compartment (1.4 mS cm1), and possibly organics were transported across the AEM from the anode to the desalination compartment with water as the carrier. However, the TOC in the three treated brackish waters showed undistinguishable concentrations of 6.9, 5.1, and 6.6 mg L1 for A, B, and C, respectively. Unlike seawater desalination in an MDC, in which osmotic pressure could
20
w a t e r r e s e a r c h 7 7 ( 2 0 1 5 ) 1 3 e2 3
reach as high as 10 atm, the back-diffusion of organics during desalinating brackish water was not affected by osmotic pressure severely. The organic gradient across the AEM were similar at about 70 mg L1 TOC when treating the three brackish waters, and this similar organic gradient was likely the major reason for the similar degree of organic contamination in the treated brackish waters.
4.3.
Model fitting and validation
To better understand the desalination behavior of brackish water in the MDC and to provide guidance for system operation, the MDC model was updated and implemented in MATLAB using ODE 23tb solver for solving stiff differential equations. The diffusion constant d was calibrated as 0.0096 mol L1 day1 with the steady state Csalt,m by an open circuit (OC) experiment (the performance was not subject to current generation, but only salt diffusion or water permeate) operated with the same MDC reactor fed with acetate as the substrate and salt solution of 5 g L1 NaCl. With initial salt concentration of 35 g L1 and external resistance of 0.1 U, the steady state Csalt,m and Jw along with the maximum water permeability (86 mL h1 m2 for AEM and 32 mL h1 m2 for CEM at 5 psi) provided by the manufacture (Membrane International, Inc.), were then used to estimate the water permeability of the ion exchange membranes used in this study. Fig. 5A shows the measured and simulated salt effluent conductivity in the MDC fed with acetate, and with 5 g L1 or 35 g L1 NaCl as the initial salt concentration at different external resistance loads. The two different salt concentrations were selected to represent the brackish water and seawater salinity (seawater was studied here for comparison purpose). The different external resistance loads allowed the evaluation of the model performance affected by current variation, as well as the concentration difference between different compartments which lead to salt diffusion and water permeation. At both initial salt concentrations, the salt effluent conductivity decreased as the external resistance load decreased which led to enhancement of the current generation. The rapid reduction in conductivity (with 35 g L1 as the initial salt concentration) when external resistance was changed from 100 U to 0.1 U was because of the dramatically increased current (increment of 6.7 mA), much higher than that from OC to 100 U (3.5 mA). The current change was slow with 5 g L1 as the initial salt concentration (4 mA increment for every resistance change), and so resulted in a gradual conductivity reduction. The simulated salt effluent conductivity shows strong agreement with the measured value, with SE less than 0.8% for the initial salt concentration of 35 g L1, and SE less than 2.9% for 5 g L1, except for the case of 5 g L1 NaCl operated with 0.1 U, which has a calculated SE of 14.5%. These results indicate excellent accuracy of the improved model for both high and low salinity desalination in MDC. With the improved mathematical model, the RMSE of the dynamic salt concentration from the previous MDC with dynamic anolyte flow rates was improved from 12.12% to 5.32% of their maximum values, and from 17.57% to 13.09% when changing the external resistances (Fig. S3 and S4, supplementary information) (Ping et al., 2014). For actual brackish water desalination operated with domestic wastewater in this study, the parameters related to
Fig. 5 e Experimental data and model prediction of the MDC performance: (A) synthetic NaCl solution at two different salinities with different applied external resistance; and (B) three brackish waters at different HRT. anodophilic and methanogenic miroorganisms were adopted from the previous model, and then adjusted with the experimental results obtained in this study. The maximum attainable current was estimated to be 5 mA by both the microbial growth mode in domestic wastewater and the low conductivity of wastewater (1 mS cm1) and brackish water. Given the weaker activity of anodophilic microorganisms in domestic wastewater, the parameter values of maximum substrate consumption rate by anodophilic microorganisms ks,a,max, half-saturation concentrations for the anodophillic microorganism Ka, half-saturation concentrations for the methanomaximum anodophilic genic microorganism Km, microorganism growth rate ka,max, and mediator yield YM were modified to 3.06 mg-S mg-a1 day1, 80 mg-S L1, 100 mgS L1, 0.164 d1, 2.83 mg-M mg-S1. The steady state performance at the longest HRT (the brackish water A at HRT of 6.9 d and brackish waters B&C at HRT of 1.7 d) was used to estimate model parameters (mainly transfer coefficient factor a), while other HRTs were for model validation (Fig. 5B). As discussed previously, longer HRT provided more treatment time, and thus resulted in lower effluent salt conductivity. The results showed excellent agreement between measured and simulated salt effluent conductivity (Fig. 5B), with the highest SE of 3.82% for the brackish water A, 4.96% for the brackish water B, and 10.7% for the brackish water C. The ionic composition was also well predicted by the model. Using the brackish water A as an example, its ionic composition in the desalinated effluent showed normalized RMSE of 5.21% (at HRT of 0.8 d), 15.2% (1.7 d), and 17.7% (6.9 d). The predicted concentrations of Ca2þ, Mg2þ, and SO2 4 were relatively higher than the measured values at HRTs of 6.9 d and 1.7 d, and the discrepancy might be related to the factors of pH
w a t e r r e s e a r c h 7 7 ( 2 0 1 5 ) 1 3 e2 3
and precipitation or absorption rate of hardness ions onto the membrane (Fig. 6A and B), which phenomenon was also observed in the previous study (Luo et al., 2012b). The pH of the brackish water A ranged from 7.49 to 8.51, and the higher pH in that range could accelerate the precipitation of those ions on the membrane, which was a complicated process that could not be predicted by the present model. The scaling on the ionexchange membrane probably reduced the transport ability of other ions, so that the measured Naþ concentration was higher than predicted values. However, the reason for measured Cl concentration to be lower than predicted value at HRT of 1.7 d was not clear, and it is possible the initial input Cl concentration in MATLAB was overestimated from IC result. At a shorter HRT of 0.8 d, the measured concentrations of Mg2þ and were close to the predicted values (Fig. 6C), probably SO2 4 because that the high flow rate did not allow enough time for MgSO4 to precipitate, which has a slower precipitation rate compared with CaCO3 (Ping et al., 2013). Inspired by the fact that a lower HRT in a single reactor results in a higher salt removal rate, the model simulated and compared two operational modes to identify an optimal mode for better desalination: the four-stage operation has a single feed of salt solution flowing through four MDCs in series with HRT of 1 day in each reactor, and the one-stage operation has four feed streams in parallel to four MDCs with HRT of 4 days in each reactor, respectively (Fig. 7; inset shows two operational
21
Fig. 7 e The salt concentration in the desalinated effluent in two simulated operations, four-stage, and one-stage operation, both at HRT 4 d.
modes); both systems will desalinate the same amount of salt water within the same time period. The salt concentration in the effluent decreases with the stages in the four-stage operation, while it decreases with time in the one-stage operation (Fig. 7). The four-stage operation achieves 14% improvement in salinity reduction compared with the one-stage operation. It is worth noting that more stages could exhibit better improvement, but not intensively. For example, a simulated ten-stage operation further improves the desalination by another 4%, compared with the four-stage operation. The model assumes same microorganism population and growth mode in the four reactors of both operations; however, actual application of the staging operation might result in different microorganism activities in different reactors. For example, the earlier stage will most likely have stronger anodophilic activities, because of sufficient uptake of electrons. Thus, the identified optimal operation mode will also need to be experimentally verified.
5.
Conclusions
This study has demonstrated the effective desalination of brackish water and treatment of municipal wastewater in MDCs, through integrated experiments and mathematical modeling. Given sufficient HRT, the desalinated brackish water could meet the none-restriction irrigation standard in terms of both salinity and composition of individual ions. A small amount of back diffused organics might lead to microbial contamination of the desalinated water, and postdisinfection may be required to inhibit bacteria growth. The improved mathematical model fit the experimental data fairly well, and was able to provide useful information for operation optimization. Those results encourage further investigation and development of MDC technology for combined wastewater and brackish water treatment.
Acknowledgments Fig. 6 e Experimental data and model prediction of the concentration of major ions in the desalinated brackish water A at HRT (A) 6.9 d; (B) 1.7 d, and (C) 0.8 d.
This project was financially supported by Research Grant Award No. US-4455-11 from BARD, the United States-Israel
22
w a t e r r e s e a r c h 7 7 ( 2 0 1 5 ) 1 3 e2 3
Binational Agricultural Research and Development Fund. The authors would like to thank Dr. Raphael Semiat (Technion) for providing the compositions of three brackish waters.
Appendix A. Supplementary data Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.watres.2015.03.008.
references
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Glossary a: Current efficiency aion,a: Ionic activity in the anode compartment aion,c: Ionic activity in the cathode compartment aion,m: Ionic activity in the desalination compartment AAEM: Water permeability of AEM ACEM: Water permeability of CEM Cion,in: Individual ion concentration in the salt influent
w a t e r r e s e a r c h 7 7 ( 2 0 1 5 ) 1 3 e2 3
Cion,m: Individual ion concentration in the desalination compartment Csalt,a: Salt concentration in the anode compartment Csalt,a,in: Salt concentration in the anolyte influent Csalt,c: Salt concentration in the cathode compartment Csalt,in: Salt concentration in the salt influent Csalt,m: Salt concentration in the desalination compartment d: The membrane salt transfer coefficient Danode: The dilution rates in the anode compartment Dsalt: The dilution rates in the desalination compartment F: Faraday constant i: Van't Hoff factor Ia¼1: The current when a ¼ 1 Ira,max: The current when da/dI is the greatest IMDC: Current generated by MDC Jw,a: Water flux between the desalination and anode compartment Jw,c: Water flux between the desalination and cathode compartment
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OPconc: Concentration overpotential Qanode: Flow rate of the anolyte in the anode compartment Qsalt: Flow rate of the salt solution in the desalination compartment R: Ideal gas constant Rext: External resistance Rint: Internal resistance of MDC T: MDC temperature tAEM,ion: Transport number in AEM tCEM,ion: Transport number in CEM u: Mobility of ions in solution Vanode: The volume of anode compartment Vcathode: The volume of cathode compartment Vsalt: The volume of desalination compartment Vjct: Junction potential VOC: Open circuit cell voltage that depends on the anodophilic microorganism concentration zion: Ionic charge
